Malignant Solid Neoplasm Clinical Trial
Official title:
A Pilot Study of Self-Administered Acupressure for Fatigue Among Adolescent and Young Adult (AYA) Cancer Survivors
Verified date | May 2024 |
Source | University of Michigan Rogel Cancer Center |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
This clinical trial tests the feasibility of self-administered relaxing acupressure on fatigue in adolescent and young adult (AYA) cancer survivors. Acupressure, a type of complementary or alternative medicine, is the application of pressure or localized massage to specific sites on the body to control symptoms. Relaxing acupressure has been shown to improve cancer-related fatigue (CRF) in adults, however, less is known about the impact of relaxing acupressure on CRF in AYA cancer survivors."
Status | Not yet recruiting |
Enrollment | 30 |
Est. completion date | September 1, 2026 |
Est. primary completion date | September 1, 2026 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 15 Years to 39 Years |
Eligibility | Inclusion Criteria: - 15 - 39 years old - At least three months post cancer treatment (e.g., surgery, radiation or chemotherapy). Participants receiving maintenance hormonal or targeted therapies will be allowed to enroll as determined by the study investigator - Report clinically relevant fatigue in the past seven days (Patient Reported Outcomes Measurement Information Systems [PROMIS] Fatigue 4a scores = 55) - Speak / read English - CRF started at or after the diagnosis of cancer - Completed cancer treatment within the past five years Exclusion Criteria: - Diagnosis of untreated anemia, mood disorder, or hypothyroidism - Plan to begin new pharmacological, psychological, or other treatments (i.e., physical therapy or dietary supplements) for CRF during the study. Although, participants may continue usual treatments for CRF if the treatments were initiated at least eight weeks prior to study enrollment, and the dose has not changed - Plan to become pregnant or lactating during the study period - Received acupressure or acupuncture in the past year |
Country | Name | City | State |
---|---|---|---|
United States | University of Michigan Comprehensive Cancer Center | Ann Arbor | Michigan |
Lead Sponsor | Collaborator |
---|---|
University of Michigan Rogel Cancer Center |
United States,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Recruitment rate | Self-administered acupressure implementation will be feasible if all participants are recruited over 2 years. Descriptive statistics will be used to summarize recruitment rate. | Up to 2 years | |
Primary | Adherence | Self-administered acupressure implementation will be feasible if 60% of participants complete the baseline and 6-week patient-reported measures and if 60% of acupressure group participants self-report acupressure practice for at least 27 minutes on at least 3 days per week. Descriptive statistics will be used to summarize adherence. | At 6 weeks | |
Primary | Satisfaction | Interview data will be analyzed using inductive content analysis. Perspectives of the intervention will be analyzed using inductive content analysis. | Up to week 10 | |
Primary | Change in fatigue | Measured using the Patient Reported Outcomes Measurement Information Systems Fatigue 4a questionnaire. Results are continuously scaled and appropriately analyzed by Gaussian-based statistical models. Change in fatigue will be analyzed using a Full Information Maximum Likelihood mixed-effects linear regression model. Specifically, change from baseline will be evaluated by including fixed-effects coefficients for time, treatment, and the important interaction effects that will determine whether changes from baseline are greater in the relaxing acupressure group, relative to controls. Random Y-intercepts in the model will be incorporated to accommodate the nesting of repeated observations within subject. Change in fatigue will be analyzed using a Full Information Maximum Likelihood mixed-effects linear regression model. | At baseline and up to week 10 |
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